390 citations
- New York UniversityUS4 papers
- Indiana UniversityUS3 papers
- Indiana University School of Medicine3 papers
- Case Western Reserve UniversityUS2 papers
- Harvard UniversityUS2 papers
- Johns Hopkins UniversityUS2 papers
- Massachusetts General HospitalUS2 papers
- Ohio UniversityUS2 papers
- Stanford MedicineUS2 papers
- The Ohio State UniversityUS2 papers
- The University of Texas Southwestern Medical CenterUS2 papers
- Thomas UniversityUS2 papers
17 papers
VISTA-SSM: Varying and Irregular Sampling Time-series Analysis via State Space Models
Benjamin Brindle, Thomas Derrick Hull, Matteo Malgaroli +1
We introduce VISTA, a clustering approach for multivariate and irregularly sampled time series based on a parametric state space mixture model. VISTA is specifically designed for t…
The co-varying ties between networks and item responses via latent variables
Selena Wang, Plamena Powla, Tracy Sweet +1
Relationships among teachers are known to influence their teaching-related perceptions. We study whether and how teachers' advising relationships (networks) are related to their pe…
Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine
Qiao Jin, Fangyuan Chen, Yiliang Zhou +15
Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily…
An Interpretive Framework for Narrower Immunity Under Section 230 of the Communications Decency Act
Gregory M. Dickinson
Almost all courts to interpret Section 230 of the Communications Decency Act have construed its ambiguously worded immunity provision broadly, shielding Internet intermediaries fro…
Toward Textual Internet Immunity
Gregory M. Dickinson
Internet immunity doctrine is broken. Under Section 230 of the Communications Decency Act of 1996, online entities are absolutely immune from lawsuits related to content authored b…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…